{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "using Plots, DataFrames, OnlineStats\n",
    "gadfly(); default(size=(500,300))\n",
    "df = readtable(joinpath(Pkg.dir(\"Plots\"), \"examples\", \"meetup\", \"winequality-white.csv\"), separator=';');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "y = float(df[:quality] .> 6)\n",
    "x = Array(df[:,1:11]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ProxGrad(η = 1.0)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# logistic regression\n",
    "reg = OnlineStats.ProxGrad()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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   "mimetype": "application/julia",
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